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Amino Acid Shortages as Cancer
Vulnerabilities
Aminozuur Tekorten als Kwetsbaarheden voor Kanker
Thesis
to obtain the degree of Doctor from the
Erasmus University Rotterdam
by command of the
rector magnificus
Prof.dr. R.C.M.E. Engels
and in accordance with the decision of the Doctorate Board.
The public defence shall be held on
Wednesday, 3rd June, 2020 at 13:30 hrs
by
Jianhui (Jane) Sun
Born in Longkou, China
Doctoral Committee: Promotor: Prof. dr. R. Agami Other members: Dr. F.N. Van Leeuwen Prof. dr. C.R. Berkers Prof.dr. R. Fodde
Table of Contents List of abbreviations Chapter 2 SLC1A3 contributes to L-asparaginase resistance in cancer cells Chapter 4 PYCR1 inhibition for cancer treatment Chapter 5 General discussion Summary Samenvatting List of publications List of Abbreviations ASNase L-asparaginase CRISPR Clustered Regularly Interspaced Short Palindromic Repeats SLC1A1 Solute carrier family 1 member 1 SLC1A2 Solute carrier family 1 member 2 SLC1A3 Solute carrier family 1 member 3
SLC1A6 Solute carrier family 1 member 6
SLC1A7 Solute carrier family 1 member 7
SLC25A1 Solute carrier family 25 member 1
ASNS Asparagine synthetase
EIF2AK4 (GCN2) Eukaryotic translation initiation factor 2 alpha kinase 4
ATF4 Activating transcription factor 4
TCA cycle Tricarboxylic acid cycle
ALL Acute lymphoblastic leukemia
RNA Ribonucleic acid
sgRNA Single guide RNA
DNA Deoxyribonucleic acid
cDNA Complementary DNA
MAGeCK Model-based analysis of genome-wide CRISPR-Cas9
knockout
FDR False discovery rate
TCGA The Cancer Genome Atlas
KIRC Kidney renal clear cell carcinoma
KIRP Kidney renal papillary cell carcinoma
LIHC Liver hepatocellular carcinoma
STAD Stomach adenocarcinoma
KO Knock-out
mRNA Messenger RNA
UCPH-101 C27H22N2O3
TFB-TBOA C19H17F3N2O6
LC-MS Liquid-chromatography mass spectrometry
OAA Oxaloacetic acid
UMP Uridine monophosphate
CMP Cytidine monophosphate
PEP Phosphoenolpyruvate
NADH Nicotinamide adenine dinucleotide (reduced form)
NAD+ Nicotinamide adenine dinucleotide (oxidized form)
NADPH Nicotinamide adenine dinucleotide phosphate (reduced form)
NADP+ Nicotinamide adenine dinucleotide phosphate (oxidized form)
FAD Flavin adenine dinucleotide
GSSG Glutathione disulfide
HMG-CoA 3-hydroxy-3-methylglutaryl-CoA
SREBP Sterol regulatory element-binding protein
VEGFA Vascular endothelial growth factor A
LDHA Lactate dehydrogenase A
BrdU BromodeoxyuridineChapter 2 SLC1A3 contributes to L-asparaginase resistance in cancer cells
Jianhui Sun1,2, Remco Nagel1, Esther A. Zaal3, Alejandro Piñeiro Ugalde1, Ruiqi Han1,2, Natalie
Proost4, Ji-Ying Song5, Abhijeet Pataskar1, Artur Burylo6, Haigen Fu7, Gerrit J Poelarends7,
Marieke van de Ven4, Olaf van Tellingen6, Celia R. Berkers3,8, Reuven Agami1,2,*
1
Division of Oncogenomics, Oncode institute, The Netherlands Cancer Institute, Plesmanlaan
121, 1066 CX Amsterdam, the Netherlands.
2
Department of Genetics, Erasmus University Medical Center, Wytemaweg 80, 3015 CN
Rotterdam, the Netherlands.
3
Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research,
Utrecht University, Utrecht, the Netherlands.
4
Preclinical Intervention Unit and Pharmacology Unit of the Mouse Clinic for Cancer and Ageing
(MCCA), The Netherlands Cancer Institute, Amsterdam, the Netherlands.
5
Division of Experimental Animal Pathology, The Netherlands Cancer Institute, Plesmanlaan
121, 1066CX Amsterdam, the Netherlands.
6
Division of Pharmacology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX
Amsterdam, the Netherlands.
7
Department of Chemical and Pharmaceutical Biology, University of Groningen, Groningen, The
Netherlands.
8
Department of Biochemistry and Cell Biology, Faculty of Veterinary Medicine, Utrecht
University, Utrecht, the Netherlands.
Adopted from EMBO J (2019)38: e102147
*
Correspondence and requests for materials should be addressed to RA
(r.agami@nki.nl). Tel: +31 205122079; E-mail: r.agami@nki.nl
Synopsis• Asparaginase is an effective drug for adolescent acute lymphoblastic leukemia treatment,
but toxicity and tolerance hampered further usage in patients with solid tumors.
• A genome-wide functional screen identifies SLC1A3 as a novel contributor to
asparaginase resistance in cancer cells, in addition to the known ASNS and GCN2.
• While SLC1A3 expression is typically restricted to brain tissues, high expression level is
observed in several tumor types.
• Combined SLC1A3 blockade with asparaginase treatment elicits cell cycle arrest and
apoptosis in SLC1A3 positive cancer cells.
• Replenishing intracellular aspartate and glutamate levels by SLC1A3 promotes cancer
cell proliferation and metastasis, despite asparaginase-induced shortages.Abstract L-asparaginase (ASNase) serves as an effective drug for adolescent acute lymphoblastic leukemia. However, many clinical trials indicated severe ASNase toxicity in patients with solid tumors, with resistant mechanisms not well understood. Here, we took a functional genetic approach and identified SLC1A3 as a novel contributor to ASNase resistance in cancer cells. In combination with ASNase, SLC1A3 inhibition caused cell cycle arrest or apoptosis, and myriads of metabolic vulnerabilities in tricarboxylic acid (TCA) cycle, urea cycle, nucleotides biosynthesis, energy production, oxidation homeostasis and lipid biosynthesis. SLC1A3 is an aspartate and glutamate transporter, mainly expressed in brain tissues, but high expression levels were also observed in some tumor types. Here, we demonstrate that ASNase stimulates aspartate and glutamate consumptions, and their refilling through SLC1A3 promotes cancer cell proliferation. Lastly, in vivo experiments indicated that SLC1A3 expression promoted tumor development and metastasis while negating the suppressive effects of ASNase by fueling aspartate, glutamate and glutamine metabolisms despite of asparagine shortage. Altogether, our findings identify a novel role for SLC1A3 in ASNase resistance and suggest that restrictive aspartate and glutamate uptake might improve ASNase efficacy with solid tumors.
Introduction Treating cancer with amino acid deprivation schemes has achieved limited clinical success so far. Only in acute lymphoblastic leukemia (ALL), the incorporation of L-asparaginase (ASNase) has significantly increased the overall survival rates to ~90% (Pui et al, 2009; Broome, 1961; Müller & J.Boos, 1998). ALL cells are auxotrophic for asparagine which was deaminated and depleted by the enzyme ASNase, resulting in cell cycle arrest and apoptosis in ALL cells without affecting normal tissues (Kidd, 1953; Broome, 1961; Pui et al, 2009; Ueno et al, 1997). Notably, ASNase has a dual asparagine and glutamine deaminase activity, however, its glutaminase activity was not required for anticancer effect in asparagine synthetase (ASNS) negative cancer cells (Chan et al, 2014). The therapeutic progress of ASNase in ALL had greatly encouraged its further application for solid tumors. However, many clinical trials reported intolerable toxicity in patients (Hays et al, 2013; Haskell et al, 1969). ASNS expression has been proposed as a marker for clinical prediction of ASNase resistance (Scherf et al, 2000), however, treatment of ALL with ASNase is still effective even though ASNS is expressed (Krall et al, 2016; Stams, 2003; Vander Heiden & DeBerardinis, 2017). Interestingly, aspartate metabolism was also predicted to contribute to ASNase sensitivity according to a previous study (Chen et al, 2011). Overall, with the exception of ASNS, little is known about the specific resistant mechanisms to ASNase, which has hindered the attempts to broaden ASNase’s benefits to patients with solid tumors (Hays et al, 2013; Kidd, 1953; Haskell et al, 1969; Vander Heiden & DeBerardinis, 2017). Our previous work has found that ASNase treatment of PC3, a prostate cancer cell line, triggered asparagine shortage accompanied by increased asparagine production through upregulation of ASNS, as indicated by ribosomal and transcriptional profiling (Loayza-Puch et al, 2016). This pinpointed a feedback loop under asparagine depleted conditions. Yet, PC3 cells remained proliferative despite of asparagine shortage, suggesting the involvement of other mechanisms responsible for ASNase resistance as upregulated ASNS was not sufficient for asparagine replenishment. Therefore, we used a functional genetic screen in PC3 cells to explore potential vulnerabilities in solid cancer cells to ASNase treatment. We identified SLC1A3, an aspartate/glutamate transporter, as a novel contributor in ASNase resistance, as well as tumor initiation and progression in a mice model for breast cancer metastasis.
Results A Genome-wide CRISPR-Cas9 screen identifies SLC1A3 as a novel contributor to ASNase resistance in PC3 cells To determine the optimal ASNase concentration required for performing a genome-wide functional screen, we tested a series of ASNase concentrations in PC3 cells. Fig 1A shows that ASNase at a concentration of 0.3~0.5 U/ml moderately inhibited cell proliferation. As this dosage is within the range used for asparagine depletion in some ALL patients according to previous research (Riccardi et al, 1981; Avramis & Panosyan, 2005), we performed the screen and in vitro validation under this condition. Due to its essential role in asparagine synthesis, ASNS gene was used as a positive control for the screen. As expected, CRISPR-Cas9 knockout (KO) of ASNS sensitized PC3 cells to ASNase treatment but did not affect cell proliferation under mock-treatment (Fig 1B). Next, we transduced a genome-wide CRISPR-Cas9 library, consisting of 76,441 single guide RNAs (sgRNAs) targeting 19,114 genes, into PC3 cells, which were further divided into mock and ASNase treated conditions (Fig 1C). Following 20 days of culturing, cells were harvested and subjected to deep sequencing of integrated sgRNAs and MAGeCK bioinformatics analysis of individual sgRNA abundance. Intriguingly, in addition to the expected ASNS gene, this analysis proposed 4 additional genes (FDR
SLC1A3 is mainly expressed in brain tissues (Fig EV1C), critical for the termination of excitatory neurotransmission (Kanai et al, 2013). Recent studies have highlighted the importance of SLC1A3-mediated aspartate uptake for cancer cell proliferation under hypoxia and crosstalk between cancer cells and cancer associated fibroblasts in the tumor niche (Garcia-Bermudez et al, 2018; Sullivan et al, 2018; Tajan et al, 2018; Alkan et al, 2018; Bertero et al, 2019). We also observed elevated SLC1A3 RNA levels in several tumor types from the TCGA database (especially kidney renal clear cell carcinoma (KIRC, p = 5.5 × 10-30), kidney renal papillary cell carcinoma (KIRP, p = 2.1 × 10-10), liver hepatocellular carcinoma (LIHC, p = 3.2 × 10-10) and stomach adenocarcinoma (STAD, p = 6.1 × 10-5)) (Fig EV1D). To examine the function of SLC1A3, we tested its cellular aspartate/glutamate transporting function using a radioactive labeled amino acid uptake assay as previously described (Loayza‐ Puch et al, 2017). As predicted, SLC1A3 loss-of-function reduced both aspartate and glutamate uptake in PC3 cells (Fig 1F), also leading to decreased endogenous aspartate (~8-fold) and glutamate (~1.5-fold) levels (Fig 1G). Following ASNase treatment in control PC3 cells, we observed strong depletions of both asparagine and glutamine (Fig 1G), in concordance with its known dual functions. This was followed by a significant reduction in endogenous aspartate and glutamate levels (Fig 1G), indicating a stimulated demand for aspartate and glutamate. Consequently, in SLC1A3-KO PC3 cells, aspartate and glutamate levels was further depleted under ASNase treatment (~16-fold for aspartate and ~3-fold for glutamate, Fig 1G). This observation suggests that SLC1A3-mediated aspartate and glutamate import is required for the maintenance of sufficient intracellular aspartate and glutamate pools to survive ASNase treatment. Of note, the endogenous glutamine level was significantly depleted in SLC1A3-KO PC3 cells, but this had no effect on cell proliferation in the absence of ASNase (Figs 1G and 1E). To directly test the functions of aspartate and glutamate in the context of ASNase, we supplemented SLC1A3-KO PC3 cells with cell-permeable forms of aspartate and glutamate (esterified). Fig 1H shows that both esterified aspartate and esterified glutamate, but not esterified leucine, can restore SLC1A3-KO PC3 cell proliferation in the presence of ASNase. Lastly, we examined a possible role of SLC1A3 to ASNase treatment in vivo. We subcutaneously implanted control and SLC1A3-KO PC3 cells into Balb/c nude mice (cAnN/Rj) and examined tumor growth in the absence and presence of ASNase. Fig EV1E shows that loss of SLC1A3 in combination of ASNase treatment impeded tumor growth. Altogether, we conclude that SLC1A3 expression negates the impact of ASNase on PC3 cell survival, proliferation and efficient tumor growth.
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ime o rsFigure 1. A genome-wide CRISPR-Cas9 screen identifies SLC1A3 as a contributor to L-
asparaginase (ASNase) resistance in PC3 cells.
A. IncuCyte cell proliferation curves of PC3 cells treated with the indicated concentrations of
ASNase.
B. IncuCyte cell proliferation curves for ASNS knockout (sgASNS) and control (sgNon-targeting)
PC3 cells in the absence and presence of ASNase.
C. Flow chart for a genome-wide CRISPR-Cas9 functional screen in PC3 cells.
D. Volcano plots for the MAGeCK pipeline analysis of the sgRNA abundance from the screen.
Green dots indicate positive controls and red dots indicate candidates with a fold discovery rate
(FDR)B). The exceptions in our cohort were LNCaP, SUM159PT and BT549 cells, with low SLC1A3 mRNA level but high basal aspartate uptake capacity. This can be explained by the relatively high expression of other aspartate/glutamate transporters in these cells (Fig 2C). Accordingly, SLC1A3-KO reduced aspartate uptake level only in SLC1A3-expressing cancer cells (Figs 2A– B). Interestingly, the sensitivity profiles of the tested cancer cell lines to ASNase treatment were generally consistent with the impact of SLC1A3-KO on aspartate uptake, with the exception of BT549 cells (Figs 2B and 2D). To further confirm the correlation between aspartate/glutamate uptake capacity and ASNase sensitivity, we used SLC1A3-deficient MCF7 cells (breast cancer cell line) and DU145 cells (prostate cancer cell line), and established two cancer cell lines overexpressing SLC1A3: MCF7-V5-SLC1A3 and DU145-V5-SLC1A3. Figs 2E–G verified SLC1A3 ectopic expression, its subcellular localization to the plasma membrane, and its capacity to uptake up aspartate in those two cell lines. Importantly, acquired ASNase resistance was observed in both cell lines after the ectopic expression of SLC1A3 (Fig 2H). In line with the above results, the addition of cell-permeable aspartate and glutamate, but not esterified leucine, to DU145 cells, restored cell proliferation under ASNase conditions (Fig 2I). Taken together, we conclude that SLC1A3-mediated aspartate/glutamate uptake promoted ASNase resistance.
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ime o rs ime o rsFigure 2. SLC1A3 expression is linked to ASNase resistance in different cancer cells.
A. RT-qPCR analysis was used to determine the relative SLC1A3 mRNA expression (to GAPDH) in
different prostate and breast cancer cell lines, as indicated.
B. The same cell lines (as in panel A) were transduced with either control (sgNon-targeting) or
sgSLC1A3. Aspartate uptake levels were determined and compared between control and
SLC1A3 KO in these cell lines. Leucine uptake level was used for normalization. The numbers
above the control column denote the basal aspartate uptake capacity.
C. RT-qPCR was used to determine the relative mRNA levels (to GAPDH) of aspartate/glutamate
transporter genes (SLC1A1, SLC1A2, SLC1A3, SLC1A6 and SLC1A7) in LNCaP, BT549 and
SUM159PT cells.
D. The same batch of cancer cells (as in panel B) was subjected to IncuCyte cell proliferation assays
in the absence or presence of ASNase at indicated concentrations ‘ns’ indicates no si nificant
difference.
E. MCF7 and DU145 cells were transduced with either lentiviral empty vector (control) or lentiviral
vector containing a V5-tagged SLC1A3 coding sequence (V5-SLC1A3). Relative SLC1A3 mRNA
levels (to GAPDH) were determined by RT-qPCR.
F. Immunofluorescence staining of the V5-tagged SLC1A3 in MCF7 and DU145 cells using anti-V5
antibody. Green staining indicates the plasma membrane localization of V5-SLC1A3 and blue
DAPI staining marks the nuclei. Scale bar stands for 5 m.
G. Relative aspartate uptake levels in control and V5-SLC1A3-expressed MCF7 and DU145 cells.
Leucine uptake level was used for normalization.
H. Control and V5-SLC1A3 expressed MCF7 and DU145 cells were subjected to IncuCyte cell
proliferation assays with or without ASNase at indicated concentrations.
I. DU145 cells were supplemented with cell-permeable aspartate (6mM, esterified) or glutamate
(3mM, esterified) following ASNase treatment, with esterified leucine (6mM or 3mM) as control.
Data information: Results were calculated based on three replicates (except for SUM159 and BT549 in B,
n=2) and presented as mean ± SD. The p-value was calculated by two-tailed unpaired t test in Prism7.
**pnanomolar level (Fig EV2A). Therefore, we used TFB-TBOA for further experiments. Notably, while TFB-TBOA and ASNase respectively had either no or mild effect on PC3 cell proliferation, their combinational treatment effectively hindered cell proliferation and cell cycle progression (Figs 3A–B and EV2B–D). In addition, TFB-TBOA completely restored the adverse effect of ASNase in DU145-V5-SLC1A3 cells but had no influence on DU145 wildtype cells (Figs 3A and 3C). Interestingly, while the combinational treatment impaired cell cycle progression in PC3 cells, it caused apoptosis in DU145-V5-SLC1A3 cells (Figs 3C and EV2E). Next, we investigated the effects of combined ASNase and SLC1A3 inhibition on intracellular amino acids and key metabolites levels by liquid-chromatography mass spectrometry (LC-MS). In concordance with SLC1A3-KO, SLC1A3 inhibition by TFB-TBOA promoted further depletions of aspartate and glutamate pools in PC3 cells in the presence of ASNase (Fig 3D). However, in contrast to SLC1A3-KO, TFB- OA didn’t pert rb aspartate, l tamate and l tamine le els, probably due to the short drug exposure time compared with the genetic manipulation. Notably, combined ASNase and SLC1A3 inhibition induced a marked reduction in argininosuccinate from the urea cycle (Fig 3E). This effect can be reasoned by the lack of aspartate availability as a substrate for argininosuccinate synthesis (Rabinovich et al, 2015). Moreover, nucleotide synthesis and tricarboxylic acid (TCA) cycle replenishments were also impaired (Fig 3E), probably due to the deficit of aspartate as previously described (Rabinovich et al, 2015; Ahn & Metallo, 2015). We also observed that combinational treatment disturbed the NAD+/NADH homeostasis, an important indicator for cellular energy assessment and oxidative status (Fig 3E). And strong lactate depletion was detected, at least partly due to the depletion of NADH (Fig 3E). Moreover, levels of carnitine metabolites (important transporters for lipid metabolism) was also perturbed under combinational conditions (Fig 3E). Above all, in SLC1A3 expressed PC3 cells, ASNase and TFB-TBOA impact metabolites involved in the urea cycle, nucleotides synthesis, energy production by TCA cycle and glycolysis, as well as oxidative homeostasis and lipid metabolism. These metabolic alterations further explain why PC3 cells resist ASNase treatment but become vulnerable once SLC1A3 is either genetically depleted or chemically blocked. We also probed the key metabolites in DU145 and DU145-V5-SLC1A3 cells. In DU145 cells (lacking SLC1A3 expression), ASNase alone was sufficient to induce a similar metabolic profile as obtained in PC3 treated with ASNase and SLC1A3 inhibition (Figs EV2F). Ectopic
expression of SLC1A3 negated these adverse effects, and accordingly, the addition of TFB- TBOA restored those perturbations in DU145-V5-SLC1A3 cells (Figs EV2F). Then we inquired whether ASNase treatment promotes a special usage of cellular aspartate/glutamate. For that purpose, we conducted metabolic flux studies using [13C4,15N] L- aspartate and [13C5,15N] L-glutamate in DU145-V5-SLC1A3 cells. Notably, as observed before (Sullivan et al, 2018), exogenous labeled aspartate was barely incorporated to the intracellular asparagine pool. Instead, both labeled aspartate and glutamate were actively used to replenish downstream metabolisms, such as TCA cycle, urea cycle and nucleotide synthesis. However, following ASNase treatment, the relative profiles of labeled metabolites remained generally similar to mock treated cells, except for increased incorporation into glutamine from labeled glutamate (Fig EV3B–C). Thus, ASNase treatment did not induce significant perturbations in the general metabolic usage of aspartate and glutamate in cancer cells.
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vulnerabilities and restrains cancer cell proliferation.
A. PC3, DU145 and V5-SLC1A3-DU145 cells were subjected to ASNase and TFB-TBOA treatment
at indicated concentrations and cell proliferation was measured by IncuCyte assay.
B. PC3 cells were treated under indicated conditions for 9 days and subjected to BrdU assays to
determine cell cycle distributions. ASNase (0.3 U/ml), TFB-TBOA (5 M).
C. DU145 and V5-SLC1A3-DU145 cells were treated under indicated conditions with ASNase (0.2
U/ml) or TFB-TBOA (20M) or both, and subjected to IncuCyte analysis for apoptotic cell counts.
D. PC3 cells were treated under ASNase (0.3 U/ml), or TFB-TBOA (5 M) conditions for 3 days and
cell lysates were extracted and intracellular contents of aspartate, asparagine, glutamate and
glutamine were determined by liquid-chromatography mass spectrometry (LC-MS).
E. From the same experiment as in panel D, key metabolites involved in urea cycle, pyrimidine
synthesis, TCA cycle, oxidation, glycolysis and carnitines metabolism were determined. The
NAD+/NADH ratio of the indicated conditions was calculated and normalized to control (mean±
SEM). Dash line indicates indirect effect. TCA cycle: tricarboxylic acid cycle; OAA: oxaloacetic
acid; UMP: uridine monophosphate; CMP: cytidine monophosphate; PEP: phosphoenolpyruvate;
NADH: nicotinamide adenine dinucleotide (reduced form); NAD+: nicotinamide adenine
dinucleotide (oxidized form); NADPH: nicotinamide adenine dinucleotide phosphate (reduced
form); NADP+: nicotinamide adenine dinucleotide phosphate (oxidized form); FAD: flavin adenine
dinucleotide; GSSG: glutathione disulfide; HMG-CoA: 3-hydroxy-3-methylglutaryl-CoA.
Data information: Median peak intensity was used for raw data normalization in (D and E). Results were
calculated based on three replicates and presented as mean ± SD (unless otherwise stated). The p-value
was calculated by two-tailed unpaired t test from Prism7. *pfor example, the biosynthesis of cholesterol, steroid and mevalonate, and the gene expression related to sterol regulatory element-binding protein (SREBP), have been strongly impaired in all three cancer cell lines when SLC1A3 was either chemically blocked or intrinsically absent following ASNase treatment (Figs 4A–C). More specifically, we observed increased VEGFA mRNA levels after combinational treatment in PC3 cells (Fig EV4A), in line with previous observations that suggested a negative correlation between VEGFA and aspartate level (Garcia-Bermudez et al, 2018). Moreover, the decreased mRNA level of lactate dehydrogenase A (LHDA) can explain the depletion in lactate level measured by metabolites profiling (Fig 3E). Though ASNS mRNA level was strongly upregulated by ASNase and SLC1A3 inhibition in DU145-V5-SLC1A3 cells, still, cell death was induced (Fig EV4C). This indicates that elevated asparagine synthesis by ASNS could be insufficient to convey ASNase resistance, which might also be determined by aspartate/glutamate bioavailability. Altogether, we conclude that the transcriptomic changes (Figs 4A–C) are in concordance with metabolomic perturbations (Figs 3E and EV2F) and cellular outcomes (Figs 3A–C), indicating a novel role of SLC1A3 in cancer cell survival following ASNase treatment.
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lo p al eFigure 4. Gene expression changes pinpoint key pathways involved in SLC1A3-mediated ASNase resistance. A–C. PC3 (A), DU145 (B) and DU145-V5-SLC1A3 (C) cells were treated with ASNase (0.3 U/ml in A; 0.2 U/ml in B and C), TFB-TBOA (5 M) for 3 days as indicated and subjected to transcriptome analysis. Bioinformatics pathway or gene ontology (GO) biological process analysis was performed on the sets of genes that were upregulated or downregulated when PC3 cells were treated with ASNase and TFB-TBOA compared to mock. Transcriptome analysis was based on one biological replicate for each cell line and validated by real-time PCR experiments in Figures EV4A–C. Heatmap presents row scaled normalized read counts and the biological signaling pathway enrichment analysis was performed by ToppGene online program (Chen et al, 2009). SLC1A3 expression promotes tumor progression and ASNase resistance in a mouse model for breast cancer metastasis Next, we set up experiments to examine the role of SLC1A3 in tumor response to ASNase treatment in vivo. As a first step, we interrogated the impact of ASNase treatment on asparagine and glutamine levels in mice with human breast cancer xenografts. We orthotopically injected human breast cancer cells (SUM159PT) to mammary fat pads of NOD-Scid IL2Rg-null (NSG) mice, allowed tumors to develop to ~250 mm3 and then systemically injected 60U ASNase per day for 5 consecutive days. Remarkably, we detected very strong ASNase-induced depletions of asparagine not only in the blood, but also in the mammary fat pad tissues and even within the growing tumors (Fig 5A). However, unlike the glutaminase effect of ASNase in vitro, here we detected very modest perturbation in glutamine levels (Fig EV5A). This is probably due to the instant glutamine replenishment under in vivo conditions. ASNase treatment could potentially disturb tumor growing environment, at least in the perspective of asparagine. Next, we employed 4T1, a highly malignant mouse breast cancer cell line, for the assessment of the influence of SLC1A3 on ASNase efficacy in vivo. This cell line does not express SLC1A3 (www.biogps.org), does not take up aspartate, and accordingly shows high sensitivity to ASNase treatment (Fig EV5B). As expected, ectopic expression of SLC1A3 (4T1-V5-SLC1A3) promoted exogenous aspartate uptake and restored 4T1 proliferation in the presence of ASNase in vitro (Fig EV5B). We therefore implanted 4T1 and 4T1-V5-SLC1A3 cells into the mammary fat pad of either mock or ASNase pretreated NSG mice and measured tumor development. Intriguingly, while the growth of tumors derived from parental 4T1 cells was impaired by ASNase at an early stage (day 9 and 12), SLC1A3-expressing tumors showed no significant differences between ASNase- and mock-treatment (Figs 5B and EV5C). Moreover,
consistent with recent reports (Sullivan et al, 2018; Garcia-Bermudez et al, 2018), implantation of SLC1A3-expressing 4T1 cells resulted in relatively faster tumor growth compared to that of parental 4T1 cells (Fig EV5D). Once tumors reached the volume of ~500mm3, mastectomy was performed to remove the primary tumors. The amino acids analysis of the harvested tumor samples by mass spectrometry revealed almost complete depletion of asparagine by ASNase, regardless of SLC1A3 expression status, and slightly reduced aspartate levels in parental 4T1 cells derived tumors following ASNase treatment (Fig 5C). Intriguingly, we also observed depleted glutamine and glutamate levels in control tumors (Fig 5C). This might relate to the absence of SLC1A3 or other aspartate/glutamate transporters in 4T1 cells, which might decelerate glutamine replenishment in the presence of ASNase, at least in this model. Of note, the introduction of SLC1A3 into 4T1 cells (4T1-V5-SLC1A3) increased intratumor aspartate and glutamate levels, and further negated aspartate and glutamine depletions by ASNase treatment at the cost of glutamate consumption (Fig 5C). Following mastectomy, mice survival rate was scored. In agreement with the effect of ASNase on primary tumor establishment, mice bearing tumors derived from parental 4T1 cells survived better early after ASNase treatment than mock treated mice (Fig EV5E, left). In contrast, ASNase treatment had no effect on the survival rate of mice with SLC1A3-expressing tumors, even at early stage (Fig EV5E, right). Recently, the bioavailability of asparagine was reported to govern breast cancer metastasis, and ASNase could reduce breast cancer metastasis (Knott et al, 2018). From our results above, SLC1A3 mediated aspartate/glutamate imports could affect ASNase treatment. Therefore, we next assessed whether SLC1A3 expression could negate the inhibitory effect of ASNase on cancer cell invasion in a mouse metastasis model for human breast cancer cells as described recently (Knott et al, 2018). For this purpose, we used MDA-MB-231 human breast cancer cells whose metastasis burden was reduced by ASNase (Knott et al, 2018). Similar to 4T1 cells, MDA-MB-231 cells hardly expressed SLC1A3 (Fig 2A), did not take up aspartate and were highly sensitive to ASNase (Fig EV5F). Consistent with above results (Figs 2G–H), SLC1A3 expression increased aspartate uptake and promoted MDA-MB-231 cell proliferation in the presence of ASNase (Fig EV5F). We therefore introduced MDA-MB-231 and MDA-MB-231-V5- SLC1A3 cells intravenously into NSG mice and assessed the invasive burdens in lung and liver. As previously reported (Knott et al, 2018), ASNase treatment reduced metastasis of parental MDA-MB-231 cells to the lung (Fig 5D). In contrast, the introduction of SLC1A3 increased
metastatic burdens and overcame the inhibitory effect by ASNase (Fig 5D). Thus, we conclude that SLC1A3 expression induces tumor progression and ASNase resistance.
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A c cle ipidsFigure 5. SLC1A3 expression promotes ASNase resistance and tumor progression in a
mice model for breast cancer metastasis.
A. SUM159PT human breast cancer cells were orthotopically injected into the mammary glands of
NSG mice. Once SUM159PT tumors reached 250mm 3 volume, mice were treated with mock or
ASNase (60U per day) for 5 consecutive days (n=3). Following treatment, mice were sacrificed,
and blood, mammary glands and tumors were collected and subjected to mass spectrometry to
determine the asparagine level. Essential amino acids were used for the raw data normalization.
Data are presented as mean ± SD.
B. The mouse breast cancer cell lines 4T1 and 4T1-V5-SLC1A3 were orthotopically implanted into
the mammary glands of pretreated NSG mice. Presented is the volume measurements of arising
tumors at day 9. (n=13 mice for each group, except for 4T1+ASNase, n=12). Data are presented
as mean ± SEM.
C. From the same experiment in panel B, tumors were surgically removed once reached a volume of
~500mm3 and collected and subjected to LC-MS to determine the levels of asparagine, aspartate,
glutamine and glutamate. Leucine level was used as a control. Results are based on five tumor
samples and presented as mean ± SEM.
D. The human breast cancer cell lines MDA-MB-231 and MDA-MB-231-V5-SLC1A3 cells were
intravenously injected into pretreated NSG mice. Once mice showed breathing problems, they
were sacrificed, and lung and liver were collected and blindly scored for metastasis lesions. The
p-value was calculated by one-tailed unpaired t test in Prism7. Data are presented as mean ±
SEM (n=8).
E. A schematic model depicting how SLC1A3-mediated aspartate and glutamate uptake promotes
ASNase resistance.
Data information: The pretreatment started 2 days before the injection of cancer cells. And mice were
either injected with 60 U ASNase or saline per day. The p-value was calculated by two-tailed unpaired t
test in Prism7, unless otherwise stated. *pDiscussion Although asparagine deprivation by ASNase was discovered as an effective treatment in lymphomas approximately 5 decades ago, its clinical implementation to other tumor types failed (Clarkson et al, 1970; Pui et al, 2009; Hays et al, 2013). The resistant mechanism to ASNase treatment in solid tumors was mainly attributed to the activation of the general amino acid sensing machinery (GCN2) and asparagine synthesis by ASNS via the GCN2-ATF4-ASNS axis (Scherf et al, 2000; Ye et al, 2010; Bunpo et al, 2009; Nakamura et al, 2018). However, the e pression of ASNS in A didn’t compromise ASNase effecti it (Vander Heiden & DeBerardinis, 2017), indicating that the ubiquitous activation of the GCN2-ATF4-ASNS axis in response to nutrient deprivation might be essential, but not sufficient to induce ASNase resistance. Very recently, protein degradation was proposed to contribute to ASNase resistance in ALL (Hinze et al, 2019), however, its contribution in the context of solid tumors is not known yet. Here, we described the identification of SLC1A3, an aspartate/glutamate transporter, as a novel contributor to ASNase resistance and metastasis in cancer cells. As SLC1A3 is specifically expressed in brain tissues, this expression pattern may be beneficial to guide ASNase treatment in solid tumors. ASNase could break down both asparagine and glutamine, even though its glutaminase activity was not required for ASNS-negative cancer cells (Chan et al, 2014). Moreover, ASNase was found effective in treating solid tumors with intrinsic loss of ASNS (Li et al, 2019). We observed that in cell culture conditions, both asparagine and glutamine were robustly depleted by ASNase (Fig 1G). However, in vivo conditions, asparagine was far more effectively depleted than glutamine (Figs 5C and EV5A), probably due to the abundant bioavailability and timely replenishment of glutamine that reduced the effect of glutaminase activity of ASNase. The importance of asparagine to tumor cell survival was further highlighted in recent studies. Ye at al., has demonstrated the importance of asparagine synthesis via GCN2-ATF4 axis for tumor cell survival during nutrient deprivation (Ye et al, 2010). And it has been demonstrated the essential role of asparagine in promoting cancer cell proliferation and breast cancer metastasis (Krall et al, 2016; Pavlova et al, 2018; Knott et al, 2018). Altogether, our study provides another support for the role of asparagine in cancer biology, and puts forward the potential usage of ASNase in cancer therapy.
According to a previous study, aspartate metabolism was predicted to contribute to ASNase resistance in primary ALL samples (Chen et al, 2011). Our results that ASNase resistance could be provoked by either ectopic SLC1A3 expression or the supplementation of membrane permeable aspartate/glutamate strongly support this hypothesis (Figs 1H and 2H–I). It indicates that SLC1A3-mediated fueling of endogenous aspartate/glutamate levels is a novel contributor to ASNase resistance. Moreover, aspartate was the second most enriched amino acid (after asparagine) for genes related to epithelial-to-mesenchymal transition (Knott et al, 2018). In line with this, we observed that SLC1A3 expression could promote cancer cell metastasis, regardless of asparagine bioavailability (Figs 5D and EV5E). Even though recent studies mainly focused on SLC1A3-mediated aspartate uptake (Alkan et al, 2018; Garcia-Bermudez et al, 2018; Sullivan et al, 2018; Tajan et al, 2018), we could not exclude the role of glutamate, which could be converted to aspartate via oxidative or reductive carboxylation. This is supported by our findings that both aspartate and glutamate could rescue ASNase toxicity in SLC1A3 KO or negative cancer cells (Figs 1H and 2I). Notably, we demonstrate that SLC1A3 inhibition in combination with ASNase treatment could hinder cancer cell proliferation by inducing either cell cycle arrest or apoptosis, which was observed in ALL cells following ASNase treatment (Kidd, 1953; Broome, 1961; Pui et al, 2009; Ueno et al, 1997). Metabolic and transcriptomic profiles of cells treated with ASNase and SLC1A3 inhibition indicated numerous defects in many critical processes (Figs 3E and EV2F). Intriguingly, in addition to the well-known engagements in urea cycle, nucleotide synthesis and TCA cycle replenishments (Van Vranken & Rutter, 2015; Rabinovich et al, 2015; Sullivan et al, 2015), aspartate and glutamate metabolisms might also directly or indirectly influence energy production, oxidation homeostasis and lipid metabolism following ASNase treatment (Fig 5E). O r metabolomic and “diricore” anal ses indicated that ASNase-treated SLC1A3-expressing cancer cells and tumors still present asparagine shortage (Figs 5A and 5C) (Loayza-Puch et al, 2016). Consistent with a previous study (Sullivan et al, 2018), our metabolic flux assays demonstrated that asparagine pool was not efficiently replenished by labeled aspartate (Fig EV3A). In mammalian cells, the lack of asparaginase activity prohibits asparagine utilization for the production of other amino acids or for the biosynthesis of metabolic intermediates (Pavlova et al, 2018). Thus, intracellular asparagine seems to be mostly consumed for protein synthesis, and the cells seem to be dependent on exogenous asparagine.
Homologues of SLC1A3 (SLC1A1, SLC1A2, SLC1A6 and SLC1A7) can also transport aspartate/glutamate (Kanai et al, 2013). It remains to be further investigated whether these transporters also contribute to ASNase resistance in some cancer cells. The compound TFB- TBOA could potently inhibited SLC1A3, which leads to the negation of SLC1A3 in ASNase resistance in vitro. However, in vivo tests with TFB-TBOA showed poor pharmacokinetics activity (a sharp drop in serum levels 7 hours post injection, data not shown). Future pharmacological manipulation of TFB-TBA might be needed to improve its in vivo performance. Altogether, using a genome-wide functional genetic approach, we identified SLC1A3, an aspartate/glutamate transporter, as a key determinant in the survival of cancer cells during ASNase treatment. We pinpointed the role of aspartate/glutamate in fueling metabolic pathways related to urea cycle, nucleotide, energy production, oxidation homeostasis, lipid metabolism, and glutamine biosynthesis, in this process. Our results show that solid tumors are amendable to systemic administration of ASNase, opening the possibility of expanding ASNase benefit to solid tumors.
Materials and Methods: Cell culture The human prostate cancer cell lines (PC3, DU145, LNCaP and 22RV1) were bought from ATCC and cultured in RPMI (Thermo Fisher Scientific). The human breast cancer cell lines (MCF7, MDA-MB-231 and MDA-MB-468) were cultured in high glucose DMEM. SUM159PT cells (archived in the lab) were cultured in DMEM/F12 1:1 medium with addition of insulin (sigma, I1882-100MG, final concentration of 5 g/ml) and hydrocortisone (sigma, final concentration of 1 g/ml). BT549 cells (archived in the lab) were cultured in RPMI with insulin (final concentration of 5 g/ml). The mouse breast cancer cell line 4T1 was a gift from O. v. Tellingen (Amsterdam, the Netherlands), and cultured in DMEM (high glucose). HEK-293T packaging cell line for lentivirus production were cultured in high glucose DMEM. All the mediums were supplemented with 10% FBS, 1% penicillin/streptomycin except for SUM159PT cells (5% FBS + 1% penicillin/streptomycin). All the cells were cultured in a humidified 37°C incubator with 5% CO2 injection. IncuCyte cell proliferation assay Cells were seeded in 96-well plate (Greiner, 655090) and 3 images per well were taken every 4 hours by the IncuCyte imaging system (Essen Bioscience). Cell confluence per well was calculated by averaging the mapped areas for those 3 images. Experiments were performed with independent triplicates. Generation of SLC1A3 expression plasmid SLC1A3 cDNA was amplified from the pLX304-SLC1A3 plasmid kindly gifted by Roderick Beijersbergen (Amsterdam, the Netherlands) using the following primer sequences: ’-ACAGCGTCTAGACCGGTTAGCGCTAGCTCATTAC- ’ and ’-CGACAGTTAGCCAGAGAGCTCGCGGCCGCCGCTGT- ’ he res ltin prod ct was digested using XbaI (Roche) and NotI (Thermo Fisher Scientific) restriction enzymes and ligated into a pLenti backbone (Korkmaz et al, 2016) with compatible sticky ends. Lentivirus production and infection A third-generation lentivirus packaging system consisting of pCMV-VSV-G (Addgene#8454), pRSV-Rev (Addgene #12253) and pMDLg/pRRE (Addgene #12252) was co-transfected with lentiCRISPR v2 (addgene: #52961) containing sgRNA. Transfection was performed in HEK- 293T cells using PEI (polyethylenimine, Polysciences) and medium was refreshed after 18
hours. Virus was harvested 48 hours after transfection by snap-frozen and stored at -80°C. Target cells were incubated with virus for 24 hours and then medium was refreshed. 36 hours after virus infection, target cells were selected with either puromycin (1 g/ml) or blasticidine (5 g/ml) according to the need of the experiments. The selection stopped when no surviving cells remained in the no-transduction control plate and cells were switched to normal culture medium. CRISPR-Cas9 genome-wide screen in PC3 cells and MAGeCK analysis PC3 cells were transduced with lentivirus pools containing sgRNAs of a genome-wide CRISPR- Cas9 Brunello library (Doench et al, 2016) (addgene #73179) at a multiplicity of infection (moi) of ~ 0.3 and ~1000× representations for each guide After ~ da s’ reco er from p rom cin g/ml) selection, cells were split into two different conditions: one was subjected to ASNase treatment (0.3 U/ml, ITK) for 20 days, and the other to mock treatment. Two independently replicates were included. Subsequently, genomic DNA was isolated using the phenol-chloroform extraction protocol and sgRNAs were amplified using a two-step PCR protocol for next- generation sequencing. Libraries were sequenced in an Illumina HiSeq-2500 sequencer and raw reads were demultiplexed and analyzed using the in-house perl script XCALIBR (https://github.com/NKI-GCF/xcalibr). The individual sgRNAs abundance were further analyzed using MAGeCK (Li et al, 2014) pipeline to find genes statistically depleted during the screening. The MAGeCK software was ran with default options and the 1000 non-targeting sgRNAs included in the CRISPR-Cas9 library were used for control normalization. ist forward primer: ’- ACA CTC TTT CCC TAC ACG ACG CTC TTC CGA TCT NNN NNN GGC TTT ATA TAT CTT GTG GAA AGG ACG - ’ and first re erse primer: ’- GTG ACT GGA GTT CAG ACG TGT GCT CTT CCG ATC TAC TGA CGG GCA CCG GAG CCA ATT CC - ’ he forward primer contained a barcode NNNNNN that enabled m ltiple ing. Second forward primer: ’- AAT GAT ACG GCG ACC ACC GAG ATC TAC ACT CTT TCC CTA CAC GAC GCT CTT CCG ATC T - ’ and re erse primer: ’- CAA GCA GAA GAC GGC ATA CGA GAT CGA TGT GTG ACT GGA GTT CAG ACG TGT GCT CTT CCG ATC T - ’ Competitive cell proliferation assay PC3 parental cells were stably transfected with pLKO-H2B-GFP and mixed with plentiv2-sgRNA transfected PC3 cells (GFP-negative) at a ratio of ~3:7 and seeded into 12-well plates in the absence or presence of ASNase (0.3 U/ml). Cells were split every 3~5 days and the ratio of GFP-negative cells among the mixed population was measured by flow cytometry (Calibur, BD
Biosciences). GFP-negative cell counts at each timepoint were normalized to day 0 when the cells were initially mixed. Radioactive aspartate uptake assay Cells were counted and seeded one day before the assay in 12-well plates as described (Loayza‐Puch et al, 2017). After washed twice with PBS, cells were incubated respectively with [3H] L-leucine (in sodium-free uptake buffer) and [3H] L-aspartate (in PBS) for 5 minutes. Next, cells were washed twice with ice-cold PBS and collected with 0.1 M NaOH. The counts for radioactivity was measured by a liquid scintillation analyzer on LSC2910 PerkinElmer Counter. Leucine uptake was used for normalization. BrdU labeling For PC3 cells, a final concentration of 10 M bromodeoxyuridine (BrdU, Sigma) was added to the medium and incubated for 25 mins. Cells were harvested and fixed with 70% cold ethanol at 4°C for 30 minutes. RNase A treatment (final concentration at 0.5 mg/mL) at 37°C for 30 mins was applied. Cells were resuspended in freshly prepared HCl/0.5% Triton solution (for DNA denature) at room temperature for 20 minutes and then neutralized by 0.1 M Na2B4O7. After washed once with PBS/Tween, cells were incubated with 1:40 diluted anti-BrdU antibody (Dako) at RT for 30 mins. Cells were incubated with FITC-conjugated anti-mouse Alexa Fluor 488 secondary antibody (1:500, Dako) at RT for 30 mins in the dark. After washing another 2X, cells were then resuspended in PI (20 g/mL) solution and ready for FACS assay (at least 10,000 cells were gated for each condition). Metabolite profiling and isotope tracing 1.5 × 105 cells were seeded in 6-well plates and treated for 72 hours as indicated. After washed twice with cold PBS, cells were subjected to 1 ml lysis buffer composed of methanol/acetonitrile/H2O (2:2:1) for metabolites extractions. The lysates were collected and centrifuged at 16, 000 g (4°C) for 15 minutes and the supernatant was transferred to a new tube for further liquid-chromatography mass spectrometry (LC-MS) analysis. The LC-MS analysis procedure and parameters were used as described before (Loayza‐Puch et al, 2017). Metabolites were identified and quantified using LCquan software (Thermo Scientific) on the basis of exact mass within 5 ppm and further validated by concordance with retention times of standards. Peak intensities were normalized based on median peak intensity of total metabolites or on essential amino acids. For Fig 5A, 10 l of serum was diluted in 1 ml lysis buffer. For Figs 5A and 5C, 50~100 mg mammary fat pad tissues and tumors were ground in a
mortar under liquid nitrogen, metabolites were extracted by adding 500 l lysis buffer and sonicated for 10 mins before centrifugation. For isotope tracing experiment, 2.5 × 105 DU145-V5-SLC1A3 cells were seeded in 6-well plates. Next day, cells were exposed to either mock or ASNase (0.2 U/ml) for 48 hours, and then supplemented with either 1.5 mM [13C4,15N] L-aspartate (Cambridge Isotope Laboratories, CNLM-544-H) and 1.5 mM unlabeled glutamate (Sigma, G8415) or 1.5 mM [13C5,15N] L- glutamate (Cambridge Isotope Laboratories, CNLM-544-H) and 1.5 mM unlabeled aspartate (Bioconnect 47203.01) for 8 hours. Then the cells and the medium were harvested for further analysis as described above. Total RNA isolation Total RNA was isolated sin ris re rea ent ioline followin the man fact rer’s instr ctions Briefly, cells were washed twice with PBS and 1 ml Trisure was added for homogenization. After centrifuge, the aqueous phase was transferred to a new tube and mixed with cold isopropyl alcohol for RNA precipitation by centrifuging at 4 °C for 1 hour. RNA pellet was washed twice with 75% ethanol and finally dissolved in RNase-free water. Reverse-transcription and quantitative real-time PCR (RT-qPCR) Reverse transcription was performed with Tetro Reverse Transcriptase kit (Bioline) according to the man fact rer’s instr ctions riefl , g total RNA was used as templates for each reaction. qPCR reactions were prepared using a SensiFAST SYBR No-ROX kit (Bioline) according to the instructions and performed in the Light Cycler 480 (Roche). Primers were listed in Table EV1. Western blot analysis Cells were washed twice with PBS and lysed with 2× SDS buffer (4% SDS, 20% glycerol and 125 mM Tris PH 6.8). Next, protein levels were quantified by Pierce BCA protein assay kit (Thermo Scientific). Lysates were loaded into a separating 7.5% SDS-PAGE gel and protein was transferred to nitrocellulose membranes. After blocking with 5% milk/PBS-Tween-20 (0.2%) solution, the membrane was incubated with mouse-anti-V5 (Thermo Fisher Scientific). Proteins were visualized using the secondary fluorescence-labeled antibodies goat-anti-mouse IRDye 680 RD (LI-COR Biosciences) and scanned on the Odyssey infrared imaging system (LI-COR Biosciences). Immunofluorescence assay
Cells were grown on glass cover slips, washed twice with PBS and fixed with 2% PFA for 10 minutes at room temperature. Next, cells were permeabilized with 0.5% Triton/PBS solution, blocked with 5% FBS for 1 hour and incubated with mouse-anti-V5 (Thermo Fisher Scientific) and Alexa-488-conjugated Rabbit anti mouse secondary antibodies. Cover slips were mounted on glass slides using Vectashield containing DAPI. Images were taken with Leica confocal microscope SP5. TruSeq standard mRNA sample preparation Stranded-specific libraries were generated using the TruSeq Stranded mRNA sample preparation it ll mina followin the man fact rer’s instr ctions riefl , g of total RNA was polyA-selected using oligo-dT beads and the RNA was fragmented, random primed and reverse transcribed using SuperScript II Reverse Transcriptase kit (Invitrogen). Second strand complementar NA was then s nthesi ed, ’-adenylated and ligated to Illumina sequencing adapters, and subsequently amplified by 12 cycles of PCR. The sequencing libraries were analyzed on a 2100 Bioanalyzer using a 7500 chip (Agilent) and pooled equimolarly into a 30 nM multiplex sequencing pool. Deep sequencing Samples were sequenced on the Illumina HiSeq2500 sequencer generating 65-nuclotide single- end reads. RNA-seq analysis Sequenced reads were aligned to the human genome (hg19) using TopHat v2.0.8 (Trapnell et al, 2009). Only uniquely mapped reads were retained for further analysis. SAMTOOLS v0.1.19 (Li et al, 2009) was used to convert the BAM output to SAM format and to sort the BAM file. The read counts per gene were calculated using the HTSeq program, v0.5.4p1 (Anders et al, 2015). The DESeq package (Oshlack et al, 2010) was used to generate normalized read counts and for differential gene expression analysis. DESeq called differentially expressed genes with FDR cutoff of 0.05 and abs (FC) >1.5 were considered as significant differentially expressed genes. IncuCyte® Caspase-3/7 Green apoptosis assay Cells were pre-seeded in 96-well plate (Greiner, 655090) 48 hours before the addition of Caspase-3/7 Green Apoptosis reagent (Essen Bioscience, 4440). The green signals were captured every 4 hours and apoptotic cells were counted. Animal studies
All mice experiments were approved by the Netherlands Cancer Institute Animal Experimental Committee. For Fig EV1E, xenografts were induced by subcutaneous injection of 4 × 106 PC3 control (sgNon-targeting) and sgSLC1A3 cells (monoclonal #4-1) in one flank of Balb/c nude mice (n=8) and treatment started when tumors reached 50 mm3. For Fig 5A, 4 × 106 SUM159PT cells were resuspended in 50 l PBS and injected into the mammary gland #4 of NOD-SCID IL2R-null (jax) (NSG) mice. After tumor volumes reached ~250 mm3, mice (n=3 per group) were administrated either with mock (saline) or ASNase (60 U per day) for 5 consecutive days by intraperitoneal injections. Serum, mammary fat pad tissues and tumors were collected and snap-frozen for LC-MS analysis when the mice were sacrificed. For Fig 5B, 1 × 105 4T1 cells and 4T1-V5-SLC1A3 cells were respectively resuspended in 20 l 1:1 mix of PBS and growth factor reduced Matrigel (GeltrexTM, Gibco) and injected into 1 mammary fat pad per mouse. Mice were pre-treated for 2 days either with saline or ASNase (60 U per day) before tumor cells were introduced and the treatment was performed every day until the mice were sacrificed (n=13 per group except for the group of 4T1 treated with ASNase, n=12). Primary tumors were surgically removed once the tumor volumes reached 450–550 mm3, and mice underwent breathing challenges every day. For Fig 5D, 5 × 104 MDA-MB-231 and MDA-MB-231-V5- SLC1A3 cells (in 50 l PBS) were respectively injected into the tail veins of 2 da s’ pre-treated NSG mice (n=8 per group) and mice were sacrificed 22 days post tumor cells introduction. All the experiments were using 6~8 weeks old NSG mice (except for Fig EV1E) and mice were weighed every 2 or 3 days to monitor weight loss. For ASNase treatment, mice were intraperitoneally administrated 60 U ASNase every day till the end of the experiments. Tumor volumes were calculated by the formula V = 1/2(LW2), where L is length and W is width of the primary tumor. Histopathology analysis of lung and liver invasion Lung and liver tissues were collected and fixed in formalin fixative and embedded in paraffin. The immunohistochemistry (IHC) of vimentin (DAKO, M0725, dilution: 1:4000) was conducted on 4µm-thick sections according to standard procedures. The stained slides were examined blindly by a pathologist and the number of tumorous lesions (more than 10 cancer cells) were scored in each of the sections. The sections were reviewed with a Zeiss Axioskop2 Plus microscope (Carl Zeiss Microscopy, Jena, Germany) and images were captured with a Zeiss AxioCam HRc digital camera and processed with AxioVision 4 software (both from Carl Zeiss Vision, München, Germany). Statistics
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